TisEM - Jochem de Bresser

Frank de Meijer

  • Frank de Meijer

    Frank de Meijer

    PhD Department of Econometrics and Operations Research

    "Many societal problems can be modelled, solved and analysed using techniques from mathematics and statistics. … [It] makes me proud of our field and triggers me to continue my research."

The recently accepted paper to INFORMS Journal on Computing titled: 'SDP-based bounds for the Quadratic Cycle Cover Problem via cutting plane augmented Lagrangian methods and reinforcement learning' by Frank de Meijer and Renata Sotirov has been given a Meritorious Paper Award.

What is the main goal of your research?

The main goal of my research is to apply mathematical programming to solve complex optimization problems on networks. These problems can either be motivated by society or inspired by a more theoretical point of view. In particular, I am interested in the application of semidefinite programming techniques to tackle these challenging problems. For the math fanatics among us: semidefinite programming can be seen as a generalization of linear programming and has applications in dozens of fields, such as engineering, data science and combinatorial optimization. My goal is to utilize these semidefinite programming techniques in clever algorithms that can tackle these problems. 

How does your research contribute to understanding and solving societal problems? 

Being only a second year PhD student, I do not make myself any illusions that my work has really impacted society. However, although my own contribution as a beginner is practically zero, I do believe that the field of mathematical programming has a huge influence on society. Many societal problems can be modelled, solved and analysed using techniques from mathematics and statistics. Each OR seminar remembers me again of the numerous applications of our field, not only in operations research, but also in medical sciences, transportation, and many more. A beautiful example of the societal impact can be found in Tilburg University’s Zero Hunger Lab. This lab, driven by some of the experts in our department, uses data science to contribute to global food security. The fact that mathematics can add so much value to these type of world problems makes me proud of our field and triggers me to continue my research.

What is your main motive?

The thing that makes me most excited about the work I am doing now is its diversity. Mathematical problems have often a lot of inherited beauty and it feels exciting to dive deep into these concepts. On the other hand, as already indicated above, the number of applications seems endless. This combination between the beautiful theory and the relevant practice is a trigger for me. Although I realize that I still have to discover my own ‘style’, I appreciate projects that touch different fields. In our most recent project, besides our main branch of study, we also borrow concepts from neighbouring branches, such as randomized algorithms, graph theory and machine learning. It is especially this broad perspective that makes me learn every single day of my PhD trajectory. Last but not least, I also like the combination between teaching and doing research. Helping students during a tutorial after a morning of doing research are the most exciting working days in my opinion.

Who is your role model?

I do not really have a particular role model in mind, but of course there are lots of people that you can learn from and have an influence on your development. Before corona hit in, I was blessed to be surrounded with the many experts in our department every day. In particular, I have learned a lot from my PhD supervisor Renata Sotirov, which has a great impact on my (scientific) life by making me enthusiastic about a career in academics. When I am looking outside the borders of our university, I have to admit that I keep on getting back to the books of Alexander Schrijver, which I consider as a great contributor to the field of combinatorial optimization. However, by mentioning them in particular, I am certainly passing by many other good researchers!